Charlson comorbidity index and 1-year poor outcomes in elderly patients undergoing successful percutaneous coronary intervention: A retrospective study

Elderly patients with acute syndrome are frailer due to the burden of comorbidity. Comorbidities that increase with age result in an increased risk of mortality in patients with acute coronary syndrome (ACS). Many scales have been developed to assess the burden of comorbidity, including the Charlson Comorbidity Index (CCI). The aim of our study is to show the effect of the CCI on 1-year mortality and poor clinical outcomes in elderly patients who underwent percutaneous coronary intervention due to ACS. This single-center retrospective study included 704 patients aged 75 years and older. The study population consisted of patients who were admitted to the hospital with ACS between April 2017 and September 2021 and underwent successful percutaneous intervention. The patients were divided into 3 groups according to their CCI scores as CCI 0 (n:156), 1 (n:266), and ≥2 (n:282). Stroke development was significantly higher in patients with CCI scores ≥ 2 compared to the other 2 groups (P = .005). Mortality rates were found to be 28.4%, 7.5%, and 2.6% in patients with CCI ≥ 2, CCI 1, and CCI 0, respectively. The mortality rate of the CCI ≥ 2 group was significantly higher than those of the other 2 groups (P < .001). The multivariate Cox proportional hazard regression model showed that CCI was an independent predictor for 1-year all-cause mortality (hazard ratio: 1.632; 95% confidence interval: 1.403–1.898; P < .001). CCI may contribute to treatment and follow-up management, as it indicates a poor prognosis in elderly patients who have undergone percutaneous coronary intervention.


Introduction
The incidence of ischemic heart disease is increasing along with the aging of the world population, and it is the leading cause of death globally. Aging causes patients to be physically weaker and frailer. Therefore, old age is an independent predictor of poor prognosis in patients with acute coronary syndrome (ACS). [1] Comorbidities that increase with age result in an increased risk of mortality in patients with ACS. [2] Clinical decision-making and treatment are difficult in elderly patients with ACS because of the increased risk of mortality and additional cardiovascular events due to the burden of comorbidity.
Comorbid conditions that pose a risk for the development of cardiovascular disease should be considered as a whole. Elderly patients usually have more than 1 comorbid condition.
Thus, many scales have been developed to assess the burden of comorbidity, including the Charlson Comorbidity Index (CCI). Previous myocardial infarction, congestive heart failure, peripheral arterial disease, cerebrovascular accident or transient ischemic attack, dementia, chronic obstructive pulmonary disease, connective tissue disorder, peptic ulcer disease, liver disease, diabetes, hemiplegia, chronic kidney disease, malignant neoplasm, leukemia and lymphoma, metastatic solid tumor, and AIDS are comorbid conditions included in the CCI. Each condition is scored between 1 and 6 based on its prognostic value. The CCI has previously been used to predict prognosis in diseases such as ACS, heart failure, cerebrovascular disease, and cancer. [3][4][5][6] The aim of our study is to show the effect of the CCI on 1-year mortality and poor clinical outcomes in elderly patients who underwent percutaneous coronary intervention after ACS. Since the study was conducted in a center with 24-hour coronary angiography facilities, early percutaneous coronary intervention was performed in all of the patients. Patients who had regular cardiology outpatient visits and received dual antiplatelet therapy until the end of the follow-up period were included in the study. Patients using oral anticoagulants were excluded from the study, as they may affect clinical outcomes. Other exclusion criteria were patients who did not undergo percutaneous coronary intervention, patients who were recommended coronary bypass surgery after coronary angiography, and patients with in-hospital mortality. CCI is a widely used death assessment model. The necessary information for CCI was obtained from the hospital registry system. Age was not evaluated in the CCI score as the study population consisted of elderly patients. All-cause mortality, which was the study endpoint, was obtained from the national electronic health record system. In addition, hospital admissions due to major and minor bleeding, cerebrovascular accident, and recurrent myocardial infarction were obtained from hospital records. Major and minor hemorrhages were determined according to the International Society on Thrombosis and Hemostasis criteria. [7] Since the patient population consisted of patients over 75 years of age, it was expected that most of them would have at least 1 comorbidity. The patients were divided into 3 groups according to their CCI scores as CCI 0, 1, and ≥2.
In summarizing the data obtained from the study, descriptive statistics were tabulated as mean ± standard deviation or median, quartile 1, and quartile 3 depending on the distribution for continuous (numerical) variables. Categorical variables were summarized as numbers and percentages. The normality of numeric variables was checked with the Kolmogorov-Smirnov, test. Comparisons of the CCI groups were made using a 1-way analysis of variance when the numerical variables showed a normal distribution and a Kruskal-Wallis H test when they did not. Multiple comparisons were evaluated with the Tukey test when parametric tests were used and with the Dwass-Steel-Critchlow-Fligner test when non-parametric tests were used. Pearson chi-squared test was used for comparisons when there were 5 or more expected cells in the differences between the categorical variables according to the groups, and the Fisher-Freeman-Halton test was used for the tables when there were fewer than 5 expected cells. The association between CCI and 1-year all-cause mortality was analyzed using multivariate Cox proportional hazards regression models, and the results were expressed as hazard ratio and 95% confidence interval. The selection of variables for the multivariate analysis was based on previous reports and clinical importance. Kaplan-Meier survival analysis and a log-rank test were performed to compare 1-year all-cause mortality between the CCI groups. Statistical analyses were performed with the SPSS Version 22 for Windows (SPSS Inc, Chicago, IL), and the level of significance was considered to be .05 (P value).

Results
There were 704 patients in the study with a mean age of 82.4 ± 4.5 years. In terms of gender distribution, the study group consisted of 376 male patients (53.4%) and 328 female patients (46.6%). There were 156 (22.2%) patients in the CCI 0 group, 266 (37.8%) in the CCI 1 group, and 282 (40.0%) in the CCI ≥ 2 group. Demographics, clinical characteristics are summarized in Table 1. In terms of ACS diagnoses, non-ST elevation myocardial infarction was the most common diagnosis (380 patients, 54.0%).
Significant differences were found between the groups in terms of age and comorbidities. The patients in the CCI ≥ 2 group were older than the patients in the CCI 1 and CCI 0 groups (P < .001). There was a significant age difference between the CCI ≥ 2 and CCI 1 groups (P = .04). The groups were similar in terms of gender and Body Mass Index (P = .64 and P = .57). There were significant differences between the groups in terms of hypertension (P < .001), hyperlipidemia (P = .03), and previous coronary bypass surgery (P = .005). Patients with CCI ≥ 2 had significantly higher hypertension than patients in the CCI 1 and CCI 0 groups. The rate of hyperlipidemia was significantly higher in patients in the CCI ≥ 2 and CCI 1 groups than in patients in the CCI 0 group (P = .03). The rates of previous coronary bypass surgery were significantly higher in patients in the CCI ≥ 2 group than in patients in the other 2 groups (P = .005). There was no significant difference between the groups in terms of ACS presentations (P = .66). There was a significant difference between the groups in terms of median systolic blood pressure value, median heart rate and ejection fraction (P = .03, P = .01 and P = .03). Laboratory parameters are summarized in Table 2. Significant differences were also found between the CCI ≥ 2 and CCI 0 groups with regard to hemoglobin values (P = .03). The groups were similar in terms of other variables (P > .05).
Major bleeding was observed in 88 (12.5%) and minor bleeding in 74 (10.5%) patients in the study group. The median time to bleeding was 135 days. Target vessel revascularization was performed in 48 patients (6.8%), and stroke was observed in 64 patients (9.1%). The mortality rate of the patients in the study group was 14.8%. The clinical features and other prognostic implications of bleeding after ACS are detailed in Table 3.
As shown in Table 3, the groups were similar in terms of major and minor bleeding, time of bleeding, target vessel revascularization and time, time of stroke, and time of death (P > .05). Acute ischemic stroke development was significantly higher in patients in the CCI ≥ 2 group compared to the other 2 groups (P = .005). Mortality rates were found to be 28.4%, 7.5%, and 2.6% in patients with CCI ≥ 2, CCI 1, and CCI 0, respectively. The mortality rate of the CCI ≥ 2 group was significantly higher than those of the other 2 groups (P < .001).
The results of Cox regression analysis are presented in Table 4. The multivariate Cox proportional hazard regression model showed that CCI was an independent predictor for 1-year all-cause mortality (hazard ratio: 1.632; 95% confidence interval: 1.403-1.898; P < .001). The Kaplan-Meier survival analysis revealed differences in the all-cause mortality rates between the CCI groups at the 1-year follow-up shown in Figure 1.

Discussion
Our studied revealed the relationship between CCI, which is an indicator of comorbidity burden, and cerebrovascular accidents and all-cause mortality in a 1-year follow-up of elderly patients who underwent percutaneous coronary intervention due to ACS.
Elderly patients are more fragile due to the increasing burden of comorbidity with age, and scoring systems, which are indicators of the comorbidity burden based on this frailty, can be used to predict patients' prognosis. CCI, developed in 1987,  Table 3 Poor clinical outcomes and times of the groups at 1-yr follow-up.
Univariate Multivariate HR (95% confidence interval) HR (95% confidence interval) is still used as an indicator of the comorbidity burden. [8] While studies have shown the prognostic value of the CCI after ACS, our study stands out due to the mean age of the patients and the number of participants. [3,9] The CCI includes non-cardiovascular comorbidities, such as chronic liver diseases, malignant neoplasm, and lymphoma. Previous studies have shown that the prognosis of patients with cardio vascular diseases worsens as the comorbidity burden increases. [10] Similarly, in our study, patients with 2 or more comorbidities had worse survival rates at the 1-year follow-up. As the number of comorbidities increases, patients become more vulnerable and fragile. It has been shown that CCI, which is an indicator of comorbidity burden, has prognostic importance not only for cardiovascular diseases but also for cerebrovascular diseases, trauma, and infection. [11][12][13] Previous studies have demonstrated that the CCI is important both in the short term (e.g., in-hospital mortality) and in the long term (e.g., 2-year mortality). [14,15] The GRACE (Global Registry of Acute Coronary Events) score is used to predict in-hospital and 6-month mortality in patients with ACS. [15] However, comorbidities are ignored in the GRACE score. In our study, although there was no significant difference between the CCI groups in terms of GRACE scores, a significant difference was observed in mortality rates. This shows that apart from the GRACE score, the burden of comorbidity and comorbidity scores are also important in terms of mortality. A previous study showed that the CCI was not superior to the GRACE score at the 2-year follow-up and made no additional contribution. [15] However, the fact that the participants in that study were younger than those in our study and that patients who did not receive invasive treatment were excluded in this study due to their poor overall prognosis, probably due to the high comorbidity burden, may have caused this difference. Comorbidity indices are more important for these patients, as the comorbidity burden increases with age, which makes elderly patients more vulnerable and fragile. Another study showed that the CCI added to the GRACE risk prediction index can be useful in predicting patient prognoses. [16] In our study, as the comorbidity burden of patients who underwent percutaneous coronary intervention due to ACS increased, more cases of acute ischemic stroke were observed during the follow-up period. In previous studies, as in our study, it has been shown that more acute ischemic stroke is observed in patients as the comorbidity burden increases. [14] In our study, target vessel revascularization was higher in the patient group with a high comorbidity burden at the 1-year follow-up, although the difference was not statistically significant. The reason for the lack of a significant difference may be that the patients in our study felt less angina because they were older, or they did not feel exertional angina due to their reduced daily activities.
Further, no significant differences were found in major and minor bleeding. The fact that patients with more comorbidities are less mobile causes them to be exposed to less trauma. Moreover, they may have applied to the hospital less because of minor bleeding due to their immobility.
Our study has some limitations. First, some comorbidities (e.g., AIDS) occur in low frequencies in the general population as well as in the study population, which consisted of elderly patients. Another limitation is the underreporting of secondary diagnoses, as the data were obtained from the hospital registry system since this was a retrospective study.

Conclusion
For elderly patients, frailty is a major concern, and the biggest cause of frailty in elderly patients is the comorbidity burden, which increases with age. Previous studies have shown that Figure 1. The Kaplan-Meier survival analysis revealed differences in the all-cause mortality rates between the CCI groups. CCI = Charlson comorbidity index. www.md-journal.com the patient prognosis will be worse as the comorbidity burden increases. Although there was no difference GRACE scores between the different CCI groups in our study, patients with high CCI scores had significantly higher rates of mortality and acute ischemic stroke at the 1-year follow-up. CCI was an independent predictor for 1-year all-cause mortality. CCI may contribute to treatment and follow-up management, as it indicates a poor prognosis in elderly patients who have undergone percutaneous coronary intervention.